Structure of the Intelligent Decision Support System for Preliminary Diagnostics of Electrical Equipment

In the context of rapid development of artificial intelligence technologies, as well as taking into account the current moral and physical deterioration of electrical equipment and the vulnerability of electric power systems around the world, the issue of ensuring diagnostics is becoming critically important. And not only identifying electrical equipment faults at the time of testing, but also predicting their occurrence based on a comprehensive analysis of a number of parameters. This scientific article discusses the use of modern methods of preliminary diagnostics and generating recommendations for further operation to increase reliability and reduce the cost of using experts in this field. The methodology proposed in this study prioritizes the issues of interpreting the results, in other words, the resulting system is capable of not only issuing a conclusion on the state of electrical equipment, but also a clear scientific justification for this conclusion. This approach increases the confidence of operating personnel in the system and significantly simplifies the implementation of such a system at real facilities. Study results demonstrate high accuracy and reliability of the system. This work can form the basis for further research in the field of electric power engineering and decision support systems.